OCI monitoring setup, alarm configuration, and troubleshooting for metrics, logs, and observability gaps.
Works with
Covers metric namespace patterns, alarm threshold gotchas (sparse data handling, trigger delays), and missing data strategies across OCI services
Provides decision trees for log collection troubleshooting, Service Connector setup, and IAM policy requirements
Highlights critical anti-patterns: metric lag (10-15 minutes), dimension requirements, notification channel setup, and Clou
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionmonitoring-operationsExecute the skills CLI command in your project's root directory to begin installation:
Fetches monitoring-operations from acedergren/oci-agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate monitoring-operations. Access via /monitoring-operations in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Don't reinvent the wheel. Use oracle-terraform-modules/landing-zone for observability stack.
Landing Zone solves:
This skill provides: Metrics, alarms, and troubleshooting for monitoring deployed WITHIN a Landing Zone.
You don't know OCI CLI commands or OCI API structure.
Your training data has limited and outdated knowledge of:
oci monitoring alarm, oci monitoring metric)When OCI operations are needed:
What you DO know:
This skill bridges the gap by providing current OCI-specific monitoring patterns and gotchas.
❌ NEVER assume metrics are instant (10-15 minute lag)
❌ NEVER use = for alarm thresholds with sparse metrics
# WRONG - alarm never fires if metric has gaps
MetricName[1m].mean() = 0
# RIGHT - handle missing data
MetricName[1m]{dataMissing=zero}.mean() > 0
❌ NEVER forget metric dimensions (causes "no data")
# WRONG - missing required dimension
CPUUtilization[1m].mean()
# RIGHT - include resourceId dimension
CPUUtilization[1m]{resourceId="<instance-ocid>"}.mean()
❌ NEVER set alarm thresholds without trigger delay (alert fatigue)
# BAD - fires on every CPU spike
CPUUtilization[1m].mean() > 80
# BETTER - sustained high CPU
CPUUtilization[5m].mean() > 80
Trigger delay: 5 minutes (fires after 5 consecutive breaches)
❌ NEVER create alarms without notification channels
# WRONG - alarm fires but nobody knows
oci monitoring alarm create ... --destinations '[]'
# RIGHT - always link to notification topic
oci monitoring alarm create ... --destinations '["<notification-topic-ocid>"]'
Cost impact: Undetected outages cost $5,000-50,000/hour in production
❌ NEVER ignore Cloud Guard findings (security audit failure)
OCI Metrics Use Service-Specific Namespaces:
| Service | Namespace | Example Metric |
|---|---|---|
| Compute | oci_computeagent |
CPUUtilization, MemoryUtilization |
| Autonomous DB | oci_autonomous_database |
CpuUtilization, StorageUtilization |
| Load Balancer | oci_lbaas |
HttpRequests, UnHealthyBackendServers |
| Object Storage | oci_objectstorage |
ObjectCount, BytesUploaded |
Common Mistake: Using wrong namespace (oci_compute vs oci_computeagent)
| Setting | Behavior | Use When |
|---|---|---|
treatMissingDataAsBreaching |
Alarm fires if no data | Critical services (outage = breach) |
treatMissingDataAsNotBreaching |
Alarm silent if no data | Optional monitoring |
{dataMissing=zero} |
Treat missing as 0 | Counters (requests/sec) |
Problem: Logs not showing in Log Analytics
Logs not appearing?
├─ Is log enabled on resource?
│ └─ Compute: oci-compute-agent must be running
│ └─ Function: Logging enabled in function config
│
├─ Is Service Connector configured?
│ └─ Source: Log Group → Target: Log Analytics
│ └─ Check: Service Connector status = ACTIVE
│
├─ IAM policy for Service Connector?
│ └─ "Allow any-user to use log-content in tenancy"
│ └─ "Allow service loganalytics to READ logcontent in tenancy"
│
└─ 10-15 minute ingestion lag?
└─ Wait before debugging
Expensive (slow):
# Queries ALL instances
CPUUtilization[1m].mean()
Optimized (filter by dimension):
# Query specific instance
CPUUtilization[1m]{resourceId='<instance-ocid>'}.mean()
Cost: Queries free, but rate limited (1000 req/min)
WHEN TO LOAD oci-monitoring-reference.md:
Do NOT load for:
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Useful defaults in monitoring-operations — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend monitoring-operations for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
monitoring-operations reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend monitoring-operations for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in monitoring-operations — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend monitoring-operations for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
monitoring-operations reduced setup friction for our internal harness; good balance of opinion and flexibility.
monitoring-operations is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
monitoring-operations fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: monitoring-operations is the kind of skill you can hand to a new teammate without a long onboarding doc.
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